Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, and the description adds substantial behavioral detail beyond that: results are capped but include the true count, the matching rule matches the dashboard chip, and Counter quantities are as at day-close so an open trading day overstates shelf stock. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet complete: purpose, row shape, cap behavior, matching rule, and a critical timing caveat are each given in one well-placed sentence. No filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of explaining return values, and it does: it lists the fields per row, states that results are capped with a true count, and clarifies the reorder rule and Counter timing. This is sufficient for an agent to know what to expect and how to interpret the data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and schema coverage is 100% by virtue of an empty schema, so the baseline is 4. There is no parameter-level information to add, and the description appropriately focuses on outputs and behavior instead.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a precise verb and resource: 'Which products are at or below their reorder point right now' and labels it the 'what do I need to reorder' list. It further specifies the exact filtering rule and output fields, distinguishing it clearly from siblings like stock_level and stock_movements.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives strong contextual cues: it is a current reorder snapshot, capped with a true count, and aligned with the dashboard low-stock chip. It explains the Counter day-close timing caveat that affects interpretation. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for an agent to select it appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.